## Abstract This paper addresses the application of a data‐based mechanistic (DBM) modelling approach using transfer function models (TFMs) with non‐linear rainfall filtering to predict runoff generation from a semi‐arid catchment (795 km^2^) in Tanzania. With DBM modelling, time series of rainfall
Empirical and Data Based Modelling of Steel Technology Processes for Industrial Application
✍ Scribed by P.R. Scheller; D. Peisker
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 634 KB
- Volume
- 6
- Category
- Article
- ISSN
- 1438-1656
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✦ Synopsis
Abstract
Process models and modelling of the fundamental relationships between the process parameters and the material properties are significant for process automation. Examples taken from the liquid steel treatment, the casting and solidification process and also from the microstructure formation and thermal influence of its properties show the practice oriented modelling of individual processing steps in the manufacturing of steel. Modelling is based both on physical and chemical fundamental principles and on data‐based methods. The used data are based on own empirical investigations as well as on selected published data which are collected in the own data base.
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